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Evolving intelligent systems are useful for processing online data streams. This paper presents an evolving granular neuro-fuzzy modeling framework and an application example on the modeling of the Rossler chaos. The evolving Granular Neural Network (eGNN) is able to deal with new events of nonstationary environments using fuzzy information granules and different types of aggregation neurons. An incremental...
Fuzzy neural networks are hybrid models capable to approximate functions with high precision and to generate transparent models, enabling the extraction of valuable information from the resulting topology. In this paper we will show that the recently proposed fuzzy neural network based on weighted uninorms aggregations uniformly approximates any real functions on any compact set. We will describe...
This paper introduces a new approach for evolving fuzzy modeling based on a tree structure. The system is a fuzzy linear regression tree whose topology can be continuously updated using a statistical model selection test. A fuzzy linear regression tree is a fuzzy tree with linear model in each leaf. The evolving linear regression approach is evaluated on a forecasting problem and its performance compared...
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